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Binglin Chen – ProQuest LLC, 2022
Assessment is a key component of education. Routine grading of students' work, however, is time consuming. Automating the grading process allows instructors to spend more of their time helping their students learn and engaging their students with more open-ended, creative activities. One way to automate grading is through computer-based…
Descriptors: College Students, STEM Education, Student Evaluation, Grading
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Bamdev, Pakhi; Grover, Manraj Singh; Singla, Yaman Kumar; Vafaee, Payman; Hama, Mika; Shah, Rajiv Ratn – International Journal of Artificial Intelligence in Education, 2023
English proficiency assessments have become a necessary metric for filtering and selecting prospective candidates for both academia and industry. With the rise in demand for such assessments, it has become increasingly necessary to have the automated human-interpretable results to prevent inconsistencies and ensure meaningful feedback to the…
Descriptors: Language Proficiency, Automation, Scoring, Speech Tests
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Barrot, Jessie S. – Computer Assisted Language Learning, 2023
Despite the building up of research on the adoption of automated writing evaluation (AWE) systems, the differential effects of automated written corrective feedback (AWCF) on errors with different severity levels and gains across writing tasks remain unclear. Thus, this study fills in the vacuum by examining how AWCF through Grammarly affects…
Descriptors: Automation, Written Language, Error Correction, Feedback (Response)
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Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs
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Figen Durkaya – Shanlax International Journal of Education, 2023
The present study has been developed in order to inquire the cognitive awareness of the 2nd grade-level students of the Science Teaching program on "sensors", which has an important place in the development of the robotic and automation systems. In the study, the method of case study, which is one of the qualitative research motifs, was…
Descriptors: Preservice Teachers, Science Teachers, Grade 2, Teacher Education Programs
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Tom Bleckmann; Gunnar Friege – Knowledge Management & E-Learning, 2023
Formative assessment is about providing and using feedback and diagnostic information. On this basis, further learning or further teaching should be adaptive and, in the best case, optimized. However, this aspect is difficult to implement in reality, as teachers work with a large number of students and the whole process of formative assessment,…
Descriptors: Concept Mapping, Formative Evaluation, Automation, Feedback (Response)
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Kornwipa Poonpon; Paiboon Manorom; Wirapong Chansanam – Contemporary Educational Technology, 2023
Automated essay scoring (AES) has become a valuable tool in educational settings, providing efficient and objective evaluations of student essays. However, the majority of AES systems have primarily focused on native English speakers, leaving a critical gap in the evaluation of non-native speakers' writing skills. This research addresses this gap…
Descriptors: Automation, Essays, Scoring, English (Second Language)
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Shuxin Tan; Young Woo Cho; Wensi Xu – Interactive Learning Environments, 2023
With the rapid advance in educational technology, electronic feedback (e-feedback) has found its way to EFL writing process. The aim of this study is to investigate the effects of three e-feedback modes, that is, automated written corrective feedback (AWCF), asynchronous computer-mediated communication (ACMC), and their combination on EFL…
Descriptors: Foreign Countries, English (Second Language), Second Language Learning, Feedback (Response)
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Tessa Charles; Carl Gwilliam – Journal for STEM Education Research, 2023
STEM fields, such as physics, increasingly rely on complex programs to analyse large datasets, thus teaching students the required programming skills is an important component of all STEM curricula. Since undergraduate students often have no prior coding experience, they are reliant on error messages as the primary diagnostic tool to identify and…
Descriptors: Automation, Feedback (Response), Error Correction, Physics
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Lautt, Marinela; Asumadu, Eunice; Abdul, Nurdin; Korzaan, Melinda – Information Systems Education Journal, 2019
Atrium Limited Liability Partnership (LLP), an architectural company with over 3,000 partners, addresses the business need to collect and organize signed tax forms to assist its international partners. This case discusses the challenges associated with the current manual process, the pursuit of a solution to automate and simplify this process and…
Descriptors: Business, Taxes, Automation, Records (Forms)
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Finkelman, Matthew D.; de la Torre, Jimmy; Karp, Jeremy A. – International Journal of Testing, 2020
Cognitive diagnosis models (CDMs) have been studied as a means of providing detailed diagnostic information about the skills that have been mastered, and the skills that have not, by examinees. Prior research has examined the use of automated test assembly (ATA) alongside CDMs; however, no previous study has investigated how to perform ATA when a…
Descriptors: Cognitive Measurement, Models, Automation, Test Construction
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Noyes, Keenan; McKay, Robert L.; Neumann, Matthew; Haudek, Kevin C.; Cooper, Melanie M. – Journal of Chemical Education, 2020
Computer-assisted analysis of students' written responses to questions is becoming a possibility due to developments in technology. This could make such constructed response questions more feasible for use in large classrooms where multiple choice assessments are often considered a more practical option. In this study, we use a previously…
Descriptors: Automation, Artificial Intelligence, Computer Uses in Education, Classification
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Cole, Brian S.; Lima-Walton, Elia; Brunnert, Kim; Vesey, Winona Burt; Raha, Kaushik – Journal of Applied Testing Technology, 2020
Automatic item generation can rapidly generate large volumes of exam items, but this creates challenges for assembly of exams which aim to include syntactically diverse items. First, we demonstrate a diminishing marginal syntactic return for automatic item generation using a saturation detection approach. This analysis can help users of automatic…
Descriptors: Artificial Intelligence, Automation, Test Construction, Test Items
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El Sherif, Reem; Langlois, Alexis; Pandu, Xiao; Nie, Jian-Yun; Thomas, James; Hong, Quan Nha; Pluye, Pierre – Education for Information, 2020
Mixed studies reviews include empirical studies with diverse designs (qualitative, quantitative and mixed methods). To make the process of identifying relevant empirical studies for such reviews more efficient, we developed a mixed filter that included different keywords and subject headings for quantitative (e.g., cohort study), qualitative…
Descriptors: Automation, Classification, Qualitative Research, Statistical Analysis
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Hilal Yildiz; S. Ipek Kuru Gonen – Turkish Online Journal of Distance Education, 2024
It is imperative to use new technologies in a supportive manner to meet the learners' and teachers' demanding needs as educational environments change in the digital age. The continuous expansion of online learning and distance education opportunities responds to the demands of learners and teachers while pioneering the use of technology in…
Descriptors: Writing Evaluation, Automation, Feedback (Response), Electronic Learning
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